Storage and transmission of digital imagery generally requires a vast amount of raw data. Increased sensor resolution in spatial, temporal, and spectral dimensions further increases the requirements for the transmission of digital imagery, including storage, bandwidth and other transmission requirements. For example, an eight bit 1024-by-1024 pixel image generally requires approximately eight mega-bits of digital information, a hyperspectral scanner collecting two hundred bands of twelve bit imagery typically produces approximately two and a half gigabits of digital information for one hyperspectral image, and high-resolution twenty-four bit video at thirty frames/second would typically require about seven hundred and fifty megabits/second.
In order to address the digital imagery storage and transmission rate increases, lossy compression techniques have been developed to reduce the overall number of bits for representation of a digital image while adhering to subjective and/or quantitative image fidelity criteria. In other words, selected image information is discarded to reduce the number of bits allotted for representation of the digital image. Examples of lossy compression techniques include JPEG, MPEG variants and H.263.
Lossy compression techniques provide bit reduction in digital image representation, but typically introduce uniform distortion in the image. Generally, as the bit rate is reduced with a lossy compression technique, there is a corresponding degradation in the image quality, including blurriness, fuzziness or other visual artifact, for example.
Lossy compression techniques have also been designed that provide bit reduction with non-uniform distortion in the image. For example, regions of the image having higher energy levels are coded with a greater number of bits as compared to regions with lower energy levels. Alternatively, regions with a greater number of edges are coded with a greater number of bits as compared to regions with fewer edges. This type of region classification can be based upon a variety of metrics in addition to energy levels and edge counts, such as fractal dimension, average gray level, and statistical variance. Although these compression methods can yield improved compression performance for a wide range of imagery, sufficient intelligence is lacking to distinguish between a region for which fidelity is preferably maintained and a region for which fidelity is less important. In other words, sufficient intelligence is lacking to maintain target-specific utility of an image while reducing the transmission requirements for an image.
Accordingly, methods and apparatus are desirable for distinguishing between a region for which fidelity is preferably maintained and a region for which fidelity is less important, such that a video image is compressed with reduced transmission requirements (e.g., bandwidth and/or storage requirements) while preserving the target-specific utility of the video image. Furthermore, additional desirable features, advantages and applications of the present invention will become apparent from the foregoing background of the invention, the subsequent detailed description of a preferred exemplary embodiment and the appended claims, taken in conjunction with the accompanying drawings.